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April 20, 2012

Scientists Identify 10 Breast Cancer Sub-types with DNA analysis

Technology Review - An international team of researchers has used a combination of genomic and gene expression analyses to identify 10 subtypes of breast cancer, each of which is typified by certain genetic aberrations. The classification of cancers can help researchers and doctors better understand patients’ responses to different therapeutics as well as prioritize drug design efforts for the most deadly of molecular disruptions.

The largely Canadian and UK team studied nearly 2000 breast tumor specimens from patients whose medical conditions were tracked for as many as 20 years after the specimens were taken. The researchers analyzed the genome sequences and gene expression levels of the tumors using DNA hybridization technology to examine changes in chromosomal architecture known as “copy number aberrations.” Breast cancer exhibits many of these structural changes--abnormal repetitions of chunks of chromosomes that can greatly alter the molecular landscape of a cell.

The researchers also identified molecular changes within some of the subtypes that could one day help doctors decide how to best treat an individual’s particular tumor type. Some clinics are already using DNA analysis to “personalize” cancer treatments and studies like this can focus doctors and drug companies on the most effective molecular targets for treatment or R&D.


Nature - The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups





The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.


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